Мы можем сгруппировать по 'USERID' и получить difftime
текущего и прошедшего 'Datetime' преобразованного столбца 'date'
library(lubridate)
library(dplyr)
df1 %>%
mutate(date = mdy_hm(date)) %>% # convert to Datetime class
group_by(USERID) %>% #group by USERID
mutate(numberofdays = as.integer(difftime(date, # take the difference
lag(date, default = first(date)), unit = 'day')))
# A tibble: 8 x 5
# Groups: USERID [3]
# ID date USERID SALES numberofdays
# <int> <dttm> <dbl> <dbl> <int>
#1 1 2018-11-19 10:36:00 500 1000 0
#2 2 2018-11-19 10:41:00 520 1450 0
#3 3 2018-11-23 10:59:00 500 1390 4
#4 4 2018-11-23 11:12:00 530 1778 0
#5 5 2018-11-29 11:52:00 530 1966 6
#6 6 2018-12-05 12:23:00 520 1100 16
#7 7 2018-12-19 12:24:00 520 700 14
#8 8 2018-12-25 21:24:00 520 900 6
данные
df1 <- structure(list(ID = 1:8, date = c("11/19/2018 10:36", "11/19/2018 10:41",
"11/23/2018 10:59", "11/23/2018 11:12", "11/29/2018 11:52", "12/5/2018 12:23",
"12/19/2018 12:24", "12/25/2018 21:24"), USERID = c(500, 520,
500, 530, 530, 520, 520, 520), SALES = c(1000, 1450, 1390, 1778,
1966, 1100, 700, 900)), class = "data.frame", row.names = c(NA,
-8L))